IBM Big Data Hub

FEBRUARY 2, 2023

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics, that enable faster decision making and insights.

Data Warehouse 56

Data Warehouse Cost-Benefit Unstructured Data Data Architecture 56

Sisense

MARCH 19, 2019

Choosing the right solution to warehouse your data is just as important as how you collect data for business intelligence. To extract the maximum value from your data, it needs to be accessible, well-sorted, and easy to manipulate and store. It Offers Significant Query Speed Upgrades.

Data Warehouse 94

Data Warehouse Cost-Benefit Business Intelligence Data Processing 94

Jedox

APRIL 8, 2021

Business Intelligence (BI) and Enterprise Performance Management (EPM) solutions aim to support effective decision-making. What is Business Intelligence? Modern organizations of all types collect data. Traditional” data is being created in operational systems such as ERP, CRM, HCM and similar or related systems.

Business Intelligence 89

Business Intelligence IT Forecasting Data Warehouse 89

David Menninger's Analyst Perspectives

SEPTEMBER 16, 2021

Rapidminer is a visual enterprise data science platform that includes data extraction, data mining, deep learning, artificial intelligence and machine learning (AI/ML) and predictive analytics. It can support AI/ML processes with data preparation, model validation, results visualization and model optimization.

Data Science 340

Data Science Data Lake Data mining Deep Learning 340

AWS Big Data

APRIL 10, 2024

When data is used to improve customer experiences and drive innovation, it can lead to business growth,” – Swami Sivasubramanian , VP of Database, Analytics, and Machine Learning at AWS in With a zero-ETL approach, AWS is helping builders realize near-real-time analytics.

Data Warehouse 92

Data Warehouse Analytics Metrics Snapshot 92

Sisense

MARCH 27, 2019

To get the most out of data, companies need to analyze it as soon as it is created—when it can provide the most immediate and relevant insights. Unlike traditional models that look at historical data for patterns, real-time analytics focuses on understanding information as it arrives to help make faster, better decisions.

Business Intelligence 74

Business Intelligence Data Warehouse Predictive Modeling Visualization 74

AWS Big Data

MAY 28, 2024

Welcome back to our exciting exploration of architectural patterns for real-time analytics with Amazon Kinesis Data Streams! In this series, we streamline the process of identifying and applying the most suitable architecture for your business requirements, and help kickstart your system development efficiently with examples.

IoT 90

IoT Analytics Dashboards Data-driven 90

FineReport

JULY 22, 2021

What is business intelligence?. Business Intelligence(BI) is defined as the concept of using modern data warehouse technology, online analysis and processing technology, data mining and data display technology for data analysis to achieve business value. Free Download.

Business Intelligence 52

Business Intelligence Sales Marketing Forecasting 52

Smart Data Collective

JULY 22, 2019

Big or small, every business needs good tools to analyze data and develop the most suitable business strategy based on the information they get. Business intelligence tools are means that help companies get insights from their data and get a better understanding of what directions and trends to follow.

Business Intelligence 80

Business Intelligence Cost-Benefit Dashboards Visualization 80

CIO Business Intelligence

SEPTEMBER 14, 2023

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines that convert raw data into formats usable by data scientists, data-centric applications, and other data consumers.

Analytics 129

Analytics Data Science Unstructured Data Data mining 129

Jet Global

JUNE 5, 2019

Data drives everything in the business world, from manufacturing to supply chain logistics to retail sales to customer experience to post-sale marketing and beyond, data holds the secrets to making processes more efficient, production costs cheaper, profit margins higher and marketing campaigns more effective. READ BLOG POST.

Data mining 75

Data mining Business Intelligence OLAP Key Performance Indicator 75

IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data Science 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

IBM Big Data Hub

AUGUST 28, 2023

It’s no wonder then that Macmillan needs sophisticated business intelligence (BI) and data analytics. For more than 10 years, the publisher has used IBM Cognos Analytics to wrangle its internal and external operational reporting needs. This contributed to the need for more analytics by our users.

Publishing 50

Publishing Analytics Business Intelligence Operational Reporting 50

CIO Business Intelligence

JUNE 14, 2023

Data and big data analytics are the lifeblood of any successful business. Getting the technology right can be challenging but building the right team with the right skills to undertake data initiatives can be even harder — a challenge reflected in the rising demand for big data and analytics skills and certifications.

Big Data 124

Big Data Data Analytics Analytics Predictive Modeling 124

CIO Business Intelligence

NOVEMBER 14, 2022

A DSS leverages a combination of raw data, documents, personal knowledge, and/or business models to help users make decisions. The data sources used by a DSS could include relational data sources, cubes, data warehouses, electronic health records (EHRs), revenue projections, sales projections, and more.

Data mining 125

Data mining Data-driven Statistics OLAP 125

datapine

SEPTEMBER 27, 2022

Business leaders, developers, data heads, and tech enthusiasts – it’s time to make some room on your business intelligence bookshelf because once again, datapine has new books for you to add. We have already given you our top data visualization books , top business intelligence books , and best data analytics books.

Business Intelligence 292

Business Intelligence Data Warehouse Data Processing Data mining 292

IBM Big Data Hub

OCTOBER 16, 2023

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. Foundation models: The power of curated datasets Foundation models , also known as “transformers,” are modern, large-scale AI models trained on large amounts of raw, unlabeled data.

Risk 70

Risk Modeling Management Metadata 70

IBM Big Data Hub

APRIL 25, 2023

In a prior blog , we pointed out that warehouses, known for high-performance data processing for business intelligence, can quickly become expensive for new data and evolving workloads. To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures.

Optimization 56

Optimization Strategy Data Warehouse Cost-Benefit 56

AWS Big Data

JUNE 28, 2023

While all of this is happening—a process that can take days—data analysts can’t run interactive analysis or build dashboards, data scientists can’t build machine learning (ML) models or run predictions, and end-users can’t make data-driven decisions.

Analytics 69

Analytics Data Warehouse Data Lake Data-driven 69

AWS Big Data

MARCH 7, 2023

This post provides guidance on how to build scalable analytical solutions for gaming industry use cases using Amazon Redshift Serverless. Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. A data warehouse is one of the components in a data hub.

Analytics 71

Analytics Data Warehouse Data Lake Metadata 71

CDW Research Hub

JULY 18, 2022

While many organizations understand the business need for a data and analytics cloud platform , few can quickly modernize their legacy data warehouse due to a lack of skills, resources, and data literacy. Sirius has created a lightweight development tool to rapidly build and deploy best-practice data models.

Optimization 87

Optimization Data Lake Data Warehouse Manufacturing 87

CIO Business Intelligence

OCTOBER 13, 2023

Solutions data architect: These individuals design and implement data solutions for specific business needs, including data warehouses, data marts, and data lakes. Application data architect: The application data architect designs and implements data models for specific software applications.

Data Architecture 124

Data Architecture Data Warehouse Statistics Visualization 124

DataKitchen

AUGUST 3, 2021

The past decades of enterprise data platform architectures can be summarized in 69 words. First-generation – expensive, proprietary enterprise data warehouse and business intelligence platforms maintained by a specialized team drowning in technical debt. See the pattern?

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

Cloudera

OCTOBER 4, 2023

We can move to predictive fraud and breach prevention, greatly increasing the protection of customer data and financial assets. Without real-time analytics we won’t catch the threats until after they’ve caused significant damage. We can also benefit from real-time stock ticker analytics, and other highly monetizable data assets.

Data Warehouse 89

Data Warehouse Experimentation Cost-Benefit Dashboards 89

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 83

Enterprise Data Warehouse Snapshot Cost-Benefit 83

CIO Business Intelligence

MARCH 16, 2022

We are all familiar with the EMR (electronic medial records) adoption and maturity models designed by HIMSS (Healthcare Information and Management Systems Society). But honestly speaking, there exists no unique maturity model which measures the degree of digital transformation. CIO Middle East: Data Analytics is key in healthcare.

Technology 95

Technology Digital Transformation Business Intelligence Data Warehouse 95

CIO Business Intelligence

AUGUST 9, 2022

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines used by data scientists, data-centric applications, and other data consumers. Data engineer job description.

Analytics 119

Analytics Data Science Statistics Unstructured Data 119

Cloudera

DECEMBER 19, 2018

Data analytics priorities have shifted this year. Growth factors and business priority are ever changing. Don’t blink or you might miss what leading organizations are doing to modernize their analytic and data warehousing environments. In 2015, only 17% of organizations surveyed had big data implementations.

Data Warehouse 52

Data Warehouse Analytics Big Data Data Architecture 52

In(tegrate) the Clouds

OCTOBER 7, 2016

As the data visualization, big data, Hadoop, Spark and self-service hype gives way to IoT, AI and Machine Learning, I dug up an old parody post on the business intelligence market circa 2007-2009 when cloud analytics was just a disruptive idea. No, let’s call it business intelligence.

Business Intelligence 40

Business Intelligence OLAP Marketing Scorecard 40

Cloudera

AUGUST 31, 2021

Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform. Accenture’s Smart Data Transition Toolkit . Are you looking for your data warehouse to support the hybrid multi-cloud?

Data Warehouse 82

Data Warehouse Cost-Benefit Metadata Data-driven 82

AWS Big Data

AUGUST 7, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Tens of thousands of customers use Amazon Redshift to process exabytes of data every day to power their analytics workloads. You pay only the associated Forecast costs. View Amazon Forecast pricing for details.

Forecasting 84

Forecasting Data Warehouse Machine Learning Modeling 84

Alation

MARCH 29, 2022

Business intelligence has a long history. Today, the term describes that same activity, but on a much larger scale, as organizations race to collect, analyze, and act on data first. With remote and hybrid work on the rise, the ability to locate and leverage data and expertise — wherever it resides — is more critical than ever.

Business Intelligence 96

Business Intelligence Reporting Data mining Data-driven 96

Birst BI

OCTOBER 30, 2018

Fortunately, advances in analytic technology have made the ability to see reliably into the future a reality. Business applications & the birth of BI. Since the dawn of business applications, the fundamental purpose of these applications has been to increase the efficiency of business processes.

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

AWS Big Data

NOVEMBER 9, 2023

It allows users to write data transformation code, run it, and test the output, all within the framework it provides. Use case The Enterprise Data Analytics group of a large jewelry retailer embarked on their cloud journey with AWS in 2021. Third-party APIs – These provide analytics and survey data related to ecommerce websites.

Data Warehouse 104

Data Warehouse Testing Data Quality Reporting 104

CIO Business Intelligence

JUNE 12, 2024

Following the merger, the energy company began its digital transformation by unifying the three networks under one ERP system, SAP, with plans to eventually evolve to SAP’s S/4HANA SaaS-based model.

Digital Transformation 98

Digital Transformation Cost-Benefit Forecasting Marketing 98

CIO Business Intelligence

SEPTEMBER 12, 2022

Data from that surfeit of applications was distributed in multiple repositories, mostly traditional databases. Fazal instructed his IT team to collect every bit of data and methodically determine its use later, rather than lose “precious” data in the rush to build a massive data warehouse. “We

Data Warehouse 116

Data Warehouse Predictive Analytics Data Lake IoT 116

CDW Research Hub

JULY 27, 2021

Data volumes are growing exponentially, and traditional, on-premises data warehouses are constrained, overly complex, and costly to scale. Companies feel locked into these systems as they are often tied to business-critical operations. Reduce the total cost of ownership of the data infrastructure.

Data Warehouse 52

Data Warehouse Data Lake Data Architecture Consulting 52